Optimizing energy and throughput for MPSoCs: an integer particle swarm optimization approach

Most of recent research in multicore processor architectures has been shifted towards reconfigurable architectures due to increasing complexity of computing systems. These systems provide better application-specific energy and throughput balance with their reconfigurable behavior. They perform automatic run time resource allocation for an application as per its needs. But in terms of performance, current methodologies produce some unpredictable results because of the actual variety of the workloads. Therefore, we need optimization of the system resources usage by employing some optimization algorithms. Early research in the field of reconfigurable architecture using optimization algorithms has produced efficient results for energy consumption with the reconfiguration of cache sizes and associativity, number of cores and operating frequency. In this research, we propose particle swarm optimization (PSO) based algorithm, Integer PSO (IPSO) for design space exploration of reconfigurable computer architectures to have better energy and throughput balance. The results obtained by IPSO are evaluated by using various SPLASH-2 benchmark applications. Evaluation shows notable reduction in energy consumption without major effect on throughput. Simulation results also support the use of IPSO in design space exploration of multicore reconfigurable processor architectures.